Submitted as: development and technical paper 11 Dec 2020

Submitted as: development and technical paper | 11 Dec 2020

Review status: this preprint is currently under review for the journal GMD.

Grid-independent High Resolution Dust Emissions (v1.0) for Chemical Transport Models: Application to GEOS-Chem (version 12.5.0)

Jun Meng1,2, Randall V. Martin2,1,3, Paul Ginoux4, Melanie Hammer2,1, Melissa P. Sulprizio5, David A. Ridley6, and Aaron van Donkelaar1,2 Jun Meng et al.
  • 1Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, B3H 4R2, Canada
  • 2Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
  • 3Smithsonian Astrophysical Observatory, Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138, USA
  • 4NOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey 08540, USA
  • 5School of Engineering and Applied Science, Harvard University, Cambridge, MA 02138, USA
  • 6California Environmental Protection Agency, Sacramento, CA 95814, USA

Abstract. The nonlinear dependence of the dust saltation process on wind speed poses a challenge for models of varying resolutions. This challenge is of particular relevance for the next generation of chemical transport models with nimble capability for multiple resolutions. We develop and apply a method to harmonize dust emissions across simulations of different resolutions by generating offline grid-independent dust emissions driven by native high-resolution meteorological fields. We implement into the GEOS-Chem chemical transport model a high-resolution dust source function to generate updated offline dust emissions. These updated offline dust emissions based on high-resolution meteorological fields can better resolve weak dust source regions, such as in southern South America, southern Africa, and the southwestern United States. Identification of an appropriate dust emission strength is facilitated by the resolution independence of offline emissions. We find that the performance of simulated aerosol optical depth (AOD) versus measurements from the AERONET network and satellite remote sensing improves significantly when using the updated offline dust emissions with the total global annual dust emission strength of 2,000 Tg yr−1 rather than the standard online emissions in GEOS-Chem. The offline high-resolution dust emissions are easily implemented in chemical transport models. The source code is available online through GitHub: . The global offline high resolution dust emission inventory is freely available (see Code and Data Availability section).

Jun Meng et al.

Status: open (until 18 Feb 2021)
Status: open (until 18 Feb 2021)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Jun Meng et al.

Data sets

Global High Resolution Dust Emission Inventory for Chemical Transport Models Jun Meng, Randall V. Martin, Paul Ginoux, David A. Ridley, and Melissa P. Sulprizio

Observations of AOD and GEOS-Chem simulation model output dataset Jun Meng, Randall V. Martin, Melanie Hammer, Aaron van Donkelaar, Paul Ginoux, and David A. Ridley

Model code and software

Jun-Meng/Offline_Dust_Emissions_SourceCode_2020_v1.0 Jun Meng, Randall V. Martin, and David A. Ridley

Jun Meng et al.


Total article views: 328 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
252 72 4 328 22 1 2
  • HTML: 252
  • PDF: 72
  • XML: 4
  • Total: 328
  • Supplement: 22
  • BibTeX: 1
  • EndNote: 2
Views and downloads (calculated since 11 Dec 2020)
Cumulative views and downloads (calculated since 11 Dec 2020)

Viewed (geographical distribution)

Total article views: 300 (including HTML, PDF, and XML) Thereof 295 with geography defined and 5 with unknown origin.
Country # Views %
  • 1
Latest update: 22 Jan 2021
Short summary
Dust emissions in models, for example, GEOS-Chem, have a strong nonlinear dependence on meteorology, which means dust emissions calculated from different resolution meteorological fields are different. Offline high-resolution dust emissions with a scalable total annual dust strength, presented in this work, can be implemented into GEOS-Chem easily so that it could promote model development by harmonizing dust emissions across simulations of different resolutions.